Assessment for bone health in patients with differentiated thyroid carcinoma after postoperative thyroid-stimulating hormone suppression therapy: a new fracture risk assessment algorithm.

Purpose: The fracture risk assessment tool (FRAX) is used to assess the 10-year risk of major site and hip fractures; however, whether this tool can be applied to patients receiving levothyroxine-based thyroid-stimulating hormone (TSH) suppressive therapy for postoperative differentiated thyroid cancer (DTC) patients is yet to be clarified. Methods and design: A total of 64 patients with DTC following thyroidectomy and oral levothyroxine for TSH suppression therapy and 30 gender- and age-matched controls were collected. The fracture risk was compared between the affected groups with different TSH levels. FRAX was used to calculate the fracture risk with and without bone mineral density (BMD). The TSH level was converted to an age-weighted score to estimate the fracture risk of postoperatively differentiated thyroid cancer patients. The sensitivity, specificity, and area under the AUC curve of the traditional FRAX and the new algorithm for osteoporosis diagnosis were compared. The dual-energy X-ray bone mineral density measurement T score was used as the gold standard to diagnose osteoporosis. Results: There were 24 patients in the T ≥ -1-2.5 group, 23 in the -2.5 < T < -1 group, and 17 in the T ≤ -2.5 group. The T score of BMD in the disease group was significantly lower than that in the control group (p < 0.05). The risk of MOF and hip fracture without a T score were significantly different under various TSH levels (p < 0.05). The area under the curve (AUC) of FRAX without BMD for predicting major osteoporotic fractures (PMOF) and major hip fractures (PHF) was 0.694 and 0.683, respectively. The cutoff values were 2.15% and 0.25%, respectively. The AUC of FRAX with BMD for PMOF and PHF was 0.976 and 0.989, respectively, and the cutoff values were 4.15% and 1.1%, respectively. The AUC of FRAX without BMD for PMOF and PHF was 0.708 and 0.72, respectively, and the cutoff values were 5.5% and 1.55%, respectively. Conclusions: FRAX is suitable for postoperative DTC patients after TSH suppressive therapy. In the absence of BMD, TSH weighted by age can improve the specificity of FRAX in the diagnosis of osteoporosis in this population.

High blood galectin-3 level associated with risk of frailty in aging.

Background: Frailty is one of the most problematic expressions of population aging, but its underlying mechanism has not been fully elucidated. Circulating galectin-3 (Gal-3) is involved in the pathogenesis of many age-related diseases. This study aims to explore the influence of circulating Gal-3 on the regulation of frailty and aging and to identify the potential mechanism further. Methods: In this cross-sectional analysis, the Fried frailty phenotype (FP) was assessed among 149 community elderly residents in Shanghai. Peripheral blood mononuclear cells (PBMCs) were isolated by the Ficoll-Paque density gradient method, and differentially expressed genes (DEGs) encoding transcription factors in frailty were detected by Illumina and bioinformatics analyzed with R software. Gene Ontology (GO) enrichment analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to explore the functional roles of these DEGs and the target genes related to frailty phenotypes. The serum Gal-3 concentration was tested by enzyme-linked immunosorbent assay (ELISA). Mouse frailty phenotype was used to construct an in vivo model of frailty, after which the serum levels of circulating Gal-3 and its gene expression levels in mouse tissues were determined. Results: Participants' mean age was 72.04 ± 7.05 years. In total, 21.48% were frail and 36.91% were pre-frail. The mean serum Gal-3 concentration was 46.34 ± 17.99 ng/mL in frail participants, 32.30 ± 8.14 ng/mL in pre-frail participants, and 26.00 ± 5.87 ng/mL in non-frail individuals (p < 0.001). Significant positive correlations between serum Gal-3 level and FP score, SARC-F score, C-reactive protein (CRP), interleukin-6, etc., were observed. In addition, the KEGG pathway and GO enrichment analyses showed that 265 DEGs in PBMCs of frail participants were mainly related to inflammatory response, translation, RNA binding, protein binding, ribosome, and primary immunodeficiency. LGALS3 was identified as the overlapping gene between frailty-related DEGs and aging-related DEGs. The elevated serum Gal-3 concentration in the in vivo model of frailty was consistent with the results in participants. Conclusion: In both community-dwelling older adults and aged mice, serum Gal-3 concentration was positively correlated with frailty. This circulating mediator may be a promising indicator of frailty. Clinical trial registration: Chinese Clinical Trial Registry identifier, ChiCTR2000036399.

Rivaroxaban for the treatment of heparin-induced thrombocytopenia with thrombosis in a patient undergoing artificial hip arthroplasty: A case report.

BACKGROUND: Anticoagulation treatment after lower limb surgery is one of the key methods to avoid thrombosis, and low-molecular-weight heparin is the treatment that is most frequently used in clinical practice. But one uncommon side effect of low-molecular-weight heparin is heparin-induced thrombocytopenia (HIT), which can develop into thrombosis if not caught early or managed incorrectly. CASE SUMMARY: We present a case of a patient who underwent hip arthroplasty and experienced thrombocytopenia due to HIT on the 9th d following the application of low-molecular-weight heparin anticoagulation. We did not diagnose HIT in time and applied 1 unit of platelets to the patient, which led to thrombosis. Luckily, the patient recovered following effective and timely surgery and treatment with rivaroxaban. CONCLUSION: Patients using low-molecular-weight heparin after lower limb surgery need to have their platelet counts regularly checked. If HIT develops, platelet treatment should be given with caution.

Effects of 30% vs. 60% inspired oxygen fraction during mechanical ventilation on postoperative atelectasis: a randomised controlled trial.

BACKGROUND: There is the ongoing debate over the effect of inspired oxygen fraction (FiO2) during mechanical ventilation on postoperative atelectasis. We aimed to compare the effects of low (30%) and moderate (60%) FiO2 on postoperative atelectasis. The hypothesis of the study was that 30% FiO2 during mechanical ventilation could reduce postoperative atelectasis volume compared with 60% FiO2. METHODS: We performed a randomized controlled trial with 120 patients. Subjects were randomly assigned to receive 30% or 60% FiO2 during mechanical ventilation in a 1:1 ratio. The primary outcome was the percentage of postoperative atelectasis volume in the total lung measured using chest CT within 30 min after extubation. The secondary outcomes included different aeration region volumes, incidence of clinically significant atelectasis, and oxygenation index. RESULTS: In total, 113 subjects completed the trial, including 55 and 58 subjects in the 30% and 60% FiO2 groups, respectively. The percentage of the postoperative atelectasis volume in the 30% FiO2 group did not differ from that in the 60% FiO2 group. Furthermore, there was no significant difference in the atelectasis volume between the two groups after the missing data were imputed by multiple imputation. Additionally, there were no significant differences in the volumes of the over-aeration, normal-aeration, and poor-aeration regions between the groups. No significant differences in the incidence of clinically significant atelectasis or oxygenation index at the end of surgery were observed between the groups. CONCLUSIONS: Compared with 60% FiO2, the use of 30% FiO2 during mechanical ventilation does not reduce the postoperative atelectasis volume. TRIAL REGISTRATION: Chinese Clinical Trial Registry ( http://www.chictr.org.cn ). Identifier: ChiCTR1900021635. Date: 2 March 2019. Principal invetigator: Weidong Gu.

Accuracy Evaluation Trial of Mixed Reality-Guided Spinal Puncture Technology.

Purpose: To evaluate the accuracy of mixed reality (MR)-guided visualization technology for spinal puncture (MRsp). Methods: MRsp involved the following three steps: 1. Lumbar spine computed tomography (CT) data were obtained to reconstruct virtual 3D images, which were imported into a HoloLens (2nd gen). 2. The patented MR system quickly recognized the spatial orientation and superimposed the virtual image over the real spine in the HoloLens. 3. The operator performed the spinal puncture with structural information provided by the virtual image. A posture fixation cushion was used to keep the subjects' lateral decubitus position consistent. 12 subjects were recruited to verify the setup error and the registration error. The setup error was calculated using the first two CT scans and measuring the displacement of two location markers. The projection points of the upper edge of the L3 spinous process (L3↑), the lower edge of the L3 spinous process (L3↓), and the lower edge of the L4 spinous process (L4↓) in the virtual image were positioned and marked on the skin as the registration markers. A third CT scan was performed to determine the registration error by measuring the displacement between the three registration markers and the corresponding real spinous process edges. Results: The setup errors in the position of the cranial location marker between CT scans along the left-right (LR), anterior-posterior (AP), and superior-inferior (SI) axes of the CT bed measured 0.09 ± 0.06 cm, 0.30 ± 0.28 cm, and 0.22 ± 0.12 cm, respectively, while those of the position of the caudal location marker measured 0.08 ± 0.06 cm, 0.29 ± 0.18 cm, and 0.18 ± 0.10 cm, respectively. The registration errors between the three registration markers and the subject's real L3↑, L3↓, and L4↓ were 0.11 ± 0.09 cm, 0.15 ± 0.13 cm, and 0.13 ± 0.10 cm, respectively, in the SI direction. Conclusion: This MR-guided visualization technology for spinal puncture can accurately and quickly superimpose the reconstructed 3D CT images over a real human spine.

Comparison of 6-min walk test distance vs. estimated maximum oxygen consumption for predicting postoperative pulmonary complications in patients undergoing upper abdominal surgery: a prospective cohort study.

OBJECTIVE: The present study aims to evaluate the predictive ability of estimated maximum oxygen consumption (e[Formula: see text]O2max) and 6-min walk distance (6MWD) for postoperative pulmonary complications (PPCs) in adult surgical patients undergoing major upper abdominal surgery. METHOD: This study was conducted by collecting data prospectively from a single center. The two predictive variables in the study were defined as 6MWD and e[Formula: see text]O2max. Patients scheduled for elective major upper abdominal surgery from March 2019 to May 2021 were included. The 6MWD was measured for all patients before surgery. e[Formula: see text]O2max was calculated using the regression model of Burr, which uses 6MWD, age, gender, weight, and resting heart rate (HR) to predict aerobic fitness. The patients were categorized into PPC and non-PPC group. The sensitivity, specificity, and optimum cutoff values for 6MWD and e[Formula: see text]O2max were calculated to predict PPCs. The area under the receiver operating characteristic curve (AUC) of 6MWD or e[Formula: see text]O2max was constructed and compared using the Z test. The primary outcome measure was the AUC of 6MWD and e[Formula: see text]O2max in predicting PPCs. In addition, the net reclassification index (NRI) was calculated to assess ability of e[Formula: see text]O2max compared with 6MWT in predicting PPCs. RESULTS: A total of 308 patients were included 71/308 developed PPCs. Patients unable to complete the 6-min walk test (6MWT) due to contraindications or restrictions, or those taking beta-blockers, were excluded. The optimum cutoff point for 6MWD in predicting PPCs was 372.5 m with a sensitivity of 63.4% and specificity of 79.3%. The optimum cutoff point for e[Formula: see text]O2max was 30.8 ml/kg/min with a sensitivity of 91.6% and specificity of 79.3%. The AUC for 6MWD in predicting PPCs was 0.758 (95% confidence interval (CI): 0.694-0.822), and the AUC for e[Formula: see text]O2max was 0.912 (95%CI: 0.875-0.949). A significantly increased AUC was observed in e[Formula: see text]O2max compared to 6MWD in predicting PPCs (P < 0.001, Z = 4.713). And compared with 6MWT, the NRI of e[Formula: see text]O2max was 0.272 (95%CI: 0.130, 0.406). CONCLUSION: The results suggested that e[Formula: see text]O2max calculated from the 6MWT is a better predictor of PPCs than 6MWD in patients undergoing upper abdominal surgery and can be used as a tool to screen patients at risk of PPCs.

Dorzagliatin add-on therapy to metformin in patients with type 2 diabetes: a randomized, double-blind, placebo-controlled phase 3 trial.

Metformin, the first-line therapy for type 2 diabetes (T2D), decreases hepatic glucose production and reduces fasting plasma glucose levels. Dorzagliatin, a dual-acting orally bioavailable glucokinase activator targeting both the pancreas and liver glucokinase, decreases postprandial glucose in patients with T2D. In this randomized, double-blind, placebo-controlled phase 3 trial, the efficacy and safety of dorzagliatin as an add-on therapy to metformin were assessed in patients with T2D who had inadequate glycemic control using metformin alone. Eligible patients with T2D (n = 767) were randomly assigned to receive dorzagliatin or placebo (1:1 ratio) as an add-on to metformin (1,500 mg per day) for 24 weeks of double-blind treatment, followed by 28 weeks of open-label treatment with dorzagliatin for all patients. The primary efficacy endpoint was the change in glycated hemoglobin (HbA1c) levels from baseline to week 24, and safety was assessed throughout the trial. At week 24, the least-squares mean change from baseline in HbA1c (95% confidence interval (CI)) was -1.02% (-1.11, -0.93) in the dorzagliatin group and -0.36% (-0.45, -0.26) in the placebo group (estimated treatment difference, -0.66%; 95% CI: -0.79, -0.53; P < 0.0001). The incidence of adverse events was similar between groups. There were no severe hypoglycemia events or drug-related serious adverse events in the dorzagliatin and metformin combined therapy group. In patients with T2D who experienced inadequate glycemic control with metformin alone, dorzagliatin resulted in effective glycemic control with good tolerability and safety profile ( NCT03141073 ).

Dorzagliatin in drug-naïve patients with type 2 diabetes: a randomized, double-blind, placebo-controlled phase 3 trial.

Improving glucose sensitivity remains an unmet medical need in treating type 2 diabetes (T2D). Dorzagliatin is a dual-acting, orally bioavailable glucokinase activator that enhances glucokinase activity in a glucose-dependent manner, improves glucose-stimulated insulin secretion and demonstrates effects on glycemic control in patients with T2D. We report the findings of a randomized, double-blind, placebo-controlled phase 3 clinical trial to evaluate the efficacy and safety of dorzagliatin in patients with T2D. Eligible drug-naïve patients with T2D (n = 463) were randomly assigned to the dorzagliatin or placebo group at a ratio of 2:1 for 24 weeks of double-blind treatment, followed by 28 weeks of open-label treatment with dorzagliatin for all patients. The primary efficacy endpoint was the change in glycated hemoglobin from baseline to week 24. Safety was assessed throughout the trial. At week 24, the least-squares mean change in glycated hemoglobin from baseline (95% confidence interval) was -1.07% (-1.19%, -0.95%) in the dorzagliatin group and -0.50% (-0.68%, -0.32%) in the placebo group (estimated treatment difference, -0.57%; 95% confidence interval: -0.79%, -0.36%; P < 0.001). The incidence of adverse events was similar between the two groups. There were no severe hypoglycemia events or drug-related serious adverse events in the dorzagliatin group. In summary, dorzagliatin improved glycemic control in drug-naïve patients with T2D and showed a good tolerability and safety profile.

Stem Cell Educator therapy in type 1 diabetes: From the bench to clinical trials.

Type 1 diabetes (T1D) is an autoimmune disease that causes a deficit of pancreatic islet ß cells. Millions of individuals worldwide have T1D, and its incidence increases annually. Recent clinical trials have highlighted the limits of conventional immunotherapy in T1D and underscore the need for novel treatments that not only overcome multiple immune dysfunctions, but also help restore islet ß-cell function. To address these two key issues, we have developed a unique and novel procedure designated the Stem Cell Educator therapy, based on the immune education by cord-blood-derived multipotent stem cells (CB-SC). Over the last 10 years, this technology has been evaluated through international multi-center clinical studies, which have demonstrated its clinical safety and efficacy in T1D and other autoimmune diseases. Mechanistic studies revealed that Educator therapy could fundamentally correct the autoimmunity and induce immune tolerance through multiple molecular and cellular mechanisms such as the expression of a master transcription factor autoimmune regulator (AIRE) in CB-SC for T-cell modulation, an expression of Galectin-9 on CB-SC to suppress activated B cells, and secretion of CB-SC-derived exosomes to polarize human blood monocytes/macrophages into type 2 macrophages. Educator therapy is the leading immunotherapy to date to safely and efficiently correct autoimmunity and restore ß cell function in T1D patients.

Identification of Transcriptional Pattern Related to Immune Cell Infiltration With Gene Co-Expression Network in Papillary Thyroid Cancer.

Background: A growing body of evidence suggests that immune cell infiltration in cancer is closely related to clinical outcomes. However, there is still a lack of research on papillary thyroid cancer (PTC). Methods: Based on single-sample gene set enrichment analysis (SSGSEA) algorithm and weighted gene co-expression network analysis (WGCNA) tool, the infiltration level of immune cell and key modules and genes associated with the level of immune cell infiltration were identified using PTC gene expression data from The Cancer Genome Atlas (TCGA) database. In addition, the co-expression network and protein-protein interactions network analysis were used to identify the hub genes. Moreover, the immunological and clinical characteristics of these hub genes were verified in TCGA and GSE35570 datasets and quantitative real-time polymerase chain reaction (PCR). Finally, receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic value of hub genes. Results: Activated B cell, activated dendritic cell, CD56bright natural killer cell, CD56dim natural killer cell, Eosinophil, Gamma delta T cell, Immature dendritic cell, Macrophage, Mast cell, Monocyte, Natural killer cell, Neutrophil and Type 17 T helper cell were significantly changed between PTC and adjacent normal groups. WGCNA results showed that the black model had the highest correlation with the infiltration level of activated dendritic cells. We found 14 hub genes whose expression correlated to the infiltration level of activated dendritic cells in both TCGA and GSE35570 datasets. After validation in the TCGA dataset, the expression level of only 5 genes (C1QA, HCK, HLA-DRA, ITGB2 and TYROBP) in 14 hub genes were differentially expressed between PTC and adjacent normal groups. Meanwhile, the expression levels of these 5 hub genes were successfully validated in GSE35570 dataset. Quantitative real-time PCR results showed the expression of these 4 hub genes (except C1QA) was consistent with the results in TCGA and GSE35570 dataset. Finally, these 4 hub genes had diagnostic value to distinguish PTC and adjacent normal controls. Conclusions: HCK, HLA-DRA, ITGB2 and TYROBP may be key diagnostic biomarkers and immunotherapy targets in PTC.

Decreased default mode network functional connectivity with visual processing regions as potential biomarkers for delayed neurocognitive recovery: A resting-state fMRI study and machine-learning analysis.

Objectives: The abnormal functional connectivity (FC) pattern of default mode network (DMN) may be key markers for early identification of various cognitive disorders. However, the whole-brain FC changes of DMN in delayed neurocognitive recovery (DNR) are still unclear. Our study was aimed at exploring the whole-brain FC patterns of all regions in DMN and the potential features as biomarkers for the prediction of DNR using machine-learning algorithms. Methods: Resting-state functional magnetic resonance imaging (fMRI) was conducted before surgery on 74 patients undergoing non-cardiac surgery. Seed-based whole-brain FC with 18 core regions located in the DMN was performed, and FC features that were statistically different between the DNR and non-DNR patients after false discovery correction were extracted. Afterward, based on the extracted FC features, machine-learning algorithms such as support vector machine, logistic regression, decision tree, and random forest were established to recognize DNR. The machine learning experiment procedure mainly included three following steps: feature standardization, parameter adjustment, and performance comparison. Finally, independent testing was conducted to validate the established prediction model. The algorithm performance was evaluated by a permutation test. Results: We found significantly decreased DMN connectivity with the brain regions involved in visual processing in DNR patients than in non-DNR patients. The best result was obtained from the random forest algorithm based on the 20 decision trees (estimators). The random forest model achieved the accuracy, sensitivity, and specificity of 84.0, 63.1, and 89.5%, respectively. The area under the receiver operating characteristic curve of the classifier reached 86.4%. The feature that contributed the most to the random forest model was the FC between the left retrosplenial cortex/posterior cingulate cortex and left precuneus. Conclusion: The decreased FC of DMN with regions involved in visual processing might be effective markers for the prediction of DNR and could provide new insights into the neural mechanisms of DNR. Clinical Trial Registration: : Chinese Clinical Trial Registry, ChiCTR-DCD-15006096.

Predicting Delayed Neurocognitive Recovery After Non-cardiac Surgery Using Resting-State Brain Network Patterns Combined With Machine Learning.

Delayed neurocognitive recovery (DNR) is a common subtype of postoperative neurocognitive disorders. An objective approach for identifying subjects at high risk of DNR is yet lacking. The present study aimed to predict DNR using the machine learning method based on multiple cognitive-related brain network features. A total of 74 elderly patients (≥ 60-years-old) undergoing non-cardiac surgery were subjected to resting-state functional magnetic resonance imaging (rs-fMRI) before the surgery. Seed-based whole-brain functional connectivity (FC) was analyzed with 18 regions of interest (ROIs) located in the default mode network (DMN), limbic network, salience network (SN), and central executive network (CEN). Multiple machine learning models (support vector machine, decision tree, and random forest) were constructed to recognize the DNR based on FC network features. The experiment has three parts, including performance comparison, feature screening, and parameter adjustment. Then, the model with the best predictive efficacy for DNR was identified. Finally, independent testing was conducted to validate the established predictive model. Compared to the non-DNR group, the DNR group exhibited aberrant whole-brain FC in seven ROIs, including the right posterior cingulate cortex, right medial prefrontal cortex, and left lateral parietal cortex in the DMN, the right insula in the SN, the left anterior prefrontal cortex in the CEN, and the left ventral hippocampus and left amygdala in the limbic network. The machine learning experimental results identified a random forest model combined with FC features of DMN and CEN as the best prediction model. The area under the curve was 0.958 (accuracy = 0.935, precision = 0.899, recall = 0.900, F1 = 0.890) on the test set. Thus, the current study indicated that the random forest machine learning model based on rs-FC features of DMN and CEN predicts the DNR following non-cardiac surgery, which could be beneficial to the early prevention of DNR. Clinical Trial Registration: The study was registered at the Chinese Clinical Trial Registry (Identification number: ChiCTR-DCD-15006096).

Multi-Order Brain Functional Connectivity Network-Based Machine Learning Method for Recognition of Delayed Neurocognitive Recovery in Older Adults Undergoing Non-cardiac Surgery.

Objectives: Delayed neurocognitive recovery (DNR) seriously affects the post-operative recovery of elderly surgical patients, but there is still a lack of effective methods to recognize high-risk patients with DNR. This study proposed a machine learning method based on a multi-order brain functional connectivity (FC) network to recognize DNR. Method: Seventy-four patients who completed assessments were included in this study, in which 16/74 (21.6%) had DNR following surgery. Based on resting-state functional magnetic resonance imaging (rs-fMRI), we first constructed low-order FC networks of 90 brain regions by calculating the correlation of brain region signal changing in the time dimension. Then, we established high-order FC networks by calculating correlations among each pair of brain regions. Afterward, we built sparse representation-based machine learning model to recognize DNR on the extracted multi-order FC network features. Finally, an independent testing was conducted to validate the established recognition model. Results: Three hundred ninety features of FC networks were finally extracted to identify DNR. After performing the independent-sample T test between these features and the categories, 15 features showed statistical differences (P < 0.05) and 3 features had significant statistical differences (P < 0.01). By comparing DNR and non-DNR patients' brain region connection matrices, it is found that there are more connections among brain regions in DNR patients than in non-DNR patients. For the machine learning recognition model based on multi-feature combination, the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the classifier reached 95.61, 92.00, 66.67, and 100.00%, respectively. Conclusion: This study not only reveals the significance of preoperative rs-fMRI in recognizing post-operative DNR in elderly patients but also establishes a promising machine learning method to recognize DNR.

Preoperative Altered Spontaneous Brain Activity and Functional Connectivity Were Independent Risk Factors for Delayed Neurocognitive Recovery in Older Adults Undergoing Noncardiac Surgery.

Objectives: Recently, it has been demonstrated that patients with subtle preexisting cognitive impairment were susceptible to delayed neurocognitive recovery (DNR). This present study investigated whether preoperative alterations in gray matter volume, spontaneous activity, or functional connectivity (FC) were associated with DNR. Methods: This was a nested case-control study of older adults (≥60 years) undergoing noncardiac surgery. All patients received MRI scan at least 1 day prior to surgery. Cognitive function was assessed prior to surgery and at 7-14 days postsurgery. Preoperative gray matter volume, amplitude of low-frequency fluctuation (ALFF), and FC were compared between the DNR patients and non-DNR patients. The independent risk factors associated with DNR were identified using a multivariate logistic regression model. Results: Of the 74 patients who completed assessments, 16/74 (21.6%) had DNR following surgery. There were no differences in gray matter volume between the two groups. However, the DNR patients exhibited higher preoperative ALFF in the bilateral middle cingulate cortex (MCC) and left fusiform gyrus and lower preoperative FC between the bilateral MCC and left calcarine than the non-DNR patients. The multivariate logistic regression analysis showed that higher preoperative spontaneous activity in the bilateral MCC was independently associated with a higher risk of DNR (OR = 3.11, 95% CI, 1.30-7.45; P = 0.011). A longer education duration (OR = 0.57, 95% CI, 0.41-0.81; P = 0.001) and higher preoperative FC between the bilateral MCC and left calcarine (OR = 0.40, 95% CI, 0.18-0.92; P = 0.031) were independently correlated with a lower risk of DNR. Conclusions: Preoperative higher ALFF in the bilateral MCC and lower FC between the bilateral MCC and left calcarine were independently associated with the occurrence of DNR. The present fMRI study identified possible preoperative neuroimaging risk factors for DNR. This trial is registered with Chinese Clinical Trial Registry ChiCTR-DCD-15006096.

Premorbid Alterations of Spontaneous Brain Activity in Elderly Patients With Early Post-operative Cognitive Dysfunction: A Pilot Resting-State Functional MRI Study.

Background: Elderly patients with pre-existing cognitive impairment are susceptible to post-operative cognitive dysfunction (POCD). In this study, we investigated whether there is pre-existing local homogeneity and functional connectivity alteration in the brain before surgery for POCD patients as compared to that in non-POCD patients. Methods: Eighty elderly patients undergoing major thoracic or abdominal surgeries were recruited. Resting-state functional MRI was scanned at least 1 day before surgery. Neuropsychological tests (NPTs) were performed before surgery and at discharge, respectively. Pre-operative regional homogeneity (ReHo) and resting-state functional connectivity (RSFC) were compared between POCD patients and non-POCD patients, respectively. Partial correlation between NPTs and ReHo or RSFC was analyzed by adjusting for confounding factors. Results: Significant difference (P < 0.001, Gaussian Random Field (GRF) correction which is a multiple comparisons correction method at cluster level, cluster size > 49) in ReHo between POCD patients and non-POCD patients was detected in right hippocampus/parahippocampus. Pre-operative RSFC between right hippocampus/parahippocampus and right middle/inferior temporal gyrus increased in POCD patients (P < 0.001, GRF correction for multiple comparisons) when compared with that in non-POCD patients.RSFC significantly correlated with composite Z-score (r = 0.46, 95% CI [0.234, 0.767], P = 0.002) or Digit Symbol Substitution Test Z-scores (r = 0.31, 95% CI [0.068, 0.643], P = 0.046) after adjusting for confounding factors. Conclusions: The results suggest that premorbid alterations of spontaneous brain activity might exist in elderly patients who develop early POCD. The neural mechanism by which patients with pre-operative abnormal spontaneous activity are susceptible to POCD requires further study.

Uncovering the potential miRNAs and mRNAs in follicular variant of papillary thyroid carcinoma in the Cancer Genome Atlas database.

BACKGROUND: Understanding the molecule mechanism is a key step in the development of diagnostic and therapeutic measures of follicular variant of papillary thyroid carcinoma. The objective of this study is to identify differentially expressed miRNAs and mRNAs, shedding light on the molecule mechanism of follicular variant of papillary thyroid carcinoma. METHODS: The data of miRNA, mRNA and DNA methylation were downloaded from The Cancer Genome Atlas (TCGA) database. Differential analysis between the follicular variant of papillary thyroid carcinoma and controls was performed in terms of miRNA expression, mRNA expression and DNA methylation. The regulatory network between miRNAs and mRNAs was constructed followed by the functional analysis of these target mRNAs. Real-time fluorescence quantitative polymerase chain reaction (QRT-PCR) was used to validate the expression of identified miRNAs and mRNAs. RESULTS: Totally, up to 8 differentially expressed miRNAs, 973 differentially expressed mRNAs and 146 differentially methylated mRNAs were identified. Hsa-mir-222 (degree =33), hsa-mir-221 (degree =29), hsa-mir-214 (degree =13), hsa-mir-138-2 (degree =11) and hsa-mir-34a (degree =4) were miRNAs that regulated the most target mRNAs (such as BCL2, BCL2L11 and PEG3, ALDH1A1, PLA2R1, TFCP2L1, RAB23, TK1 and CTSB). Focal adhesion, MAPK signaling pathway and p53 signaling pathway were three significantly enriched signaling pathways of target differentially expressed mRNAs in the functional analysis. The in vitro validation of hsa-mir-222 and hsa-mir-221, CTSB, TFCP2L1 and BCL2 was consistent with the bioinformatics analysis. CONCLUSIONS: The identified altered miRNAs (hsa-mir-222, hsa-mir-221, hsa-mir-214, hsa-mir-138-2 and hsa-mir-34a) and their target mRNAs (BCL2, BCL2L11 and PEG3, ALDH1A1, PLA2R1, TFCP2L1, RAB23, TK1 and CTSB) may be helpful in understanding the molecule mechanism of follicular variant of papillary thyroid carcinoma.

Efficacy of low-protein diet for diabetic nephropathy: a systematic review of randomized controlled trials.

BACKGROUND: A low-protein diet (LPD) is believed to be beneficial in slowing the progression of kidney disease. It is reported that low protein diet can improve protein, sugar and lipid metabolism, and reduce the symptoms and complications of renal insufficiency. However, there has been controversial regarding the effects of protein restriction on diabetic nephropathy (DN). OBJECTIVE: To investigate the efficacy of LPD on renal function in patients with type 1 or 2 DN by meta-analysis of randomized controlled trials (RCTs). DESIGN: PubMed, MEDLINE, EMBASE and China National Knowledge Infrastructure databases were searched. Eleven randomized controlled trials met the inclusion criteria, of which 10 were English and 1 was Chinese. The primary outcome was a change in glomerular filtration rate (GFR). The secondary outcome was a change in proteinuria. Random-effects models were used to calculate the standardized mean difference (SMD) and the corresponding 95% confidence intervals (CI). Subgroup analyses were also performed. RESULTS: Our research indicated that LPD was not associated with a significant improvement in GFR (1.59 ml · min-1 · 1.73 m-2, 95% CI -0.57, 3.75, I2 = 76%; p = 0.15). This effect was consistent across the subgroups regardless of type of diabetes, course of diabetes and intervention period. Our results also showed that there was no significant difference on improvement of proteinuria in patients of LPD and those in normal-protein diet groups (- 0.48, 95%CI-1.70, 0.74, I2 = 94%, p = 0.44). Subgroup analysis revealed that LPD resulted in increased excretion of proteinuria in patients with type 2 diabetes (1.32, 95% CI 0.17, 2.47, I2 = 86%, p = 0.02). CONCLUSION: The present research showed that LPD was not significantly associated with improvement of renal function in patients with either type 1 or 2 diabetic nephropathy. Although these results do not completely eliminate the possibility that LPD is beneficial for patients with diabetic nephropathy, it does not seem to be significant benefit to renal function.

BRAFV600E mutation contributes papillary thyroid carcinoma and Hashimoto thyroiditis with resistance to thyroid hormone: A case report and literature review.

Resistance to thyroid hormone (RTH) is a rare autosomal hereditary disorder characterized by increased serum thyroid hormone (TH) levels with unsuppressed or increased thyrotropin concentration. It remains unknown whether the coexistence of RTH with papillary thyroid carcinoma (PTC) and Hashimoto thyroiditis (HT) is incidental or whether it possesses a genetic or pathophysiological association. In the present study, a case of RTH with PTC and HT in an 11-year-old Chinese patient was examined and the clinical presentation of RTH with PTC was discussed. In addition, the possible associations between RTH, PTC and HT were determined. HT was confirmed in the patient using an autoimmune assay and thyroid ultrasound. RTH was diagnosed on the basis of clinical manifestations, laboratory information and gene analysis, and PTC was diagnosed according to histological results. Results of BRAFV600E mutation analysis were positive. A literature review of 14 cases of RTH with PTC was included for comparison. The present case report indicates an association of RTH with PTC and HT coexistence in the patient. Close follow-up, histological evaluation and BRAFV600E mutation detection should be performed in each RTH case with HT, since a persistent increase in TSH may be a risk factor for the development of thyroid neoplasm.

Platelet-Derived Mitochondria Display Embryonic Stem Cell Markers and Improve Pancreatic Islet ß-cell Function in Humans.

Diabetes is a major global health issue and the number of individuals with type 1 diabetes (T1D) and type 2 diabetes (T2D) increases annually across multiple populations. Research to develop a cure must overcome multiple immune dysfunctions and the shortage of pancreatic islet ß cells, but these challenges have proven intractable despite intensive research effort more than the past decades. Stem Cell Educator (SCE) therapy-which uses only autologous blood immune cells that are externally exposed to cord blood stem cells adhering to the SCE device, has previously been proven safe and effective in Chinese and Spanish subjects for the improvement of T1D, T2D, and other autoimmune diseases. Here, 4-year follow-up studies demonstrated the long-term safety and clinical efficacy of SCE therapy for the treatment of T1D and T2D. Mechanistic studies found that the nature of platelets was modulated in diabetic subjects after receiving SCE therapy. Platelets and their released mitochondria display immune tolerance-associated markers that can modulate the proliferation and function of immune cells. Notably, platelets also expressed embryonic stem cell- and pancreatic islet ß-cell-associated markers that are encoded by mitochondrial DNA. Using freshly-isolated human pancreatic islets, ex vivo studies established that platelet-releasing mitochondria can migrate to pancreatic islets and be taken up by islet ß cells, leading to the proliferation and enhancement of islet ß-cell functions. These findings reveal new mechanisms underlying SCE therapy and open up new avenues to improve the treatment of diabetes in clinics. Stem Cells Translational Medicine 2017;6:1684-1697.

Blockade of the activation of T cells around ß-cell by the targeted CTLA-4 Ig at the surface of ß-cell.

Diabetes mellitus affects 347 million people worldwide, and over 80 % of diabetes deaths occur in low- and middle-income countries. Type 1 diabetes (T1D) is characterized by the attacks of the body's own immune system on the pancreatic ß-cells. In this work, we present a new CTLA-4 Ig targeting at the surface of ß-cell and prepare it from Escherichia coli aiming at clearing activated T cells around ß-cells and avoiding all-round decline in systematic immunity. This fusion protein is composed of CTLA-4-Ig part and ß-cell-targeting part, with properties of the therapeutic effect of CTLA-4-Ig and selective binding to ß-cells. In preliminary biological activity assay, our results verified the feasibility of ß-cell-targeting strategy and its activity of CTLA-4-Ig part. The fusion protein recognizes and binds specifically to CD80(+) and CD86(+) cells as well as ß-cell, but not to control cells, displaying the potential to be used as a feasible and effective treatment of T1D with lessened side effect.